Edward Meeds, Max Welling. Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. In Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, Roman Garnett, editors, Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada. pages 2080-2088, 2015. [doi]
@inproceedings{MeedsW15,
title = {Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference},
author = {Edward Meeds and Max Welling},
year = {2015},
url = {http://papers.nips.cc/paper/5881-optimization-monte-carlo-efficient-and-embarrassingly-parallel-likelihood-free-inference},
researchr = {https://researchr.org/publication/MeedsW15},
cites = {0},
citedby = {0},
pages = {2080-2088},
booktitle = {Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada},
editor = {Corinna Cortes and Neil D. Lawrence and Daniel D. Lee and Masashi Sugiyama and Roman Garnett},
}